Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution
Abstract
Diffusion-weighted magnetic resonance imaging can provide information related to the arrangement of white matter fibers. The diffusion tensor is the model most commonly used to derive the orientation of the fibers within a voxel. However, this model has been shown to fail in regions containing several fiber populations with distinct orientations. A number of alternative models have been suggested, such as multiple tensor fitting, q-space, and Q-ball imaging. However, each of these has inherent limitations. In this study, we propose a novel method for estimating the fiber orientation distribution directly from high angular resolution diffusion-weighted MR data without the need for prior assumptions regarding the number of fiber populations present. We assume that all white matter fiber bundles in the brain share identical diffusion characteristics, thus implicitly assigning any differences in diffusion anisotropy to partial volume effects. The diffusion-weighted signal attenuation measured over the surface of a sphere can then be expressed as the convolution over the sphere of a response function (the diffusion-weighted attenuation profile for a typical fiber bundle) with the fiber orientation density function (ODF). The fiber ODF (the distribution of fiber orientations within the voxel) can therefore be obtained using spherical deconvolution. The properties of the technique are demonstrated using simulations and on data acquired from a volunteer using a standard 1.5-T clinica…
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Some researchers using constrained spherical deconvolution for fibre tracking have divided the cingulum three-ways into subgenual, retrosplenial (supracallosal), and parahippocampal (ventral) components.
“Other researchers using the constrained spherical deconvolution algorithm (Tournier et al., 2004) for fibre tracking have divided the tract three-ways, e.g., into its ‘subgenual’, ‘retrosplenial’ (supracallosal), and ‘parahippocampal’ (ventral) components (Jones et al., 2013; see Fig. 6C).”
From The cingulum bundle: Anatomy, function, and dysfunction (2018) · cites this paper as Tournier et al., 2004
The TDF model addresses well-established limitations of the standard single-tensor diffusion model, which cannot resolve complex profiles of WM architecture such as crossing or mixing fibers, present in up to 90% of WM voxels.
“The TDF model addresses well-established limitations of the standard single-tensor diffusion model—which cannot resolve complex profiles of WM architecture such as crossing or mixing fibers, present in up to 90% of WM voxels (Tournier et al., 2004; Descoteaux et al., 2007, 2009; Jeurissen et al., 2013).”
From Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3 (2019) · cites this paper as Tournier et al., 2004
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- Authors
- Tournier, J.-D., Calamante, F., Gadian, D. G., & Connelly, A.
- Affiliations
- Great Ormond Street Hospital (GB)
- Corresponding author
- Tournier, J.-Donald
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2004-11
- Volume
- 23
- Issue
- 3
- Pages
- 1176-1185
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2034252184
- Cited by
- 1,635
- References
- 4
- Citations by year
- 2026: 56 · 2025: 80 · 2024: 79 · 2023: 87 · 2022: 100 · 2021: 97 · 2020: 102 · 2019: 103 · 2018: 97 · 2017: 117 · 2016: 80 · 2015: 94 · 2014: 64 · 2013: 84 · 2012: 75
- FWCI
- 22.35
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Funders
- Wellcome Trust
- Great Ormond Street Hospital for Children
- Engineering and Physical Sciences Research Council
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- spherical deconvolution, diffusion-weighted imaging, high angular resolution diffusion MRI, white matter fiber bundles, partial volume effect, tractography
- MeSH terms
- Algorithms, Brain, Computer Simulation, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Nerve Fibers, Anisotropy, Diffusion Magnetic Resonance Imaging
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